Impact Factors Research for Carbon Emissions of Transportation Industry Based on Shapley Decomposition Method-an Analysis of Liaoning Province

旅游城镇化不可转移生态足迹演变及驱动因素

Investigation of carbon dioxide emission in China by primary component analysis

This paper investigates the relationship between carbon dioxide emissions and the influence factors in China. Eight affecting factors, namely, population (P), urban population (UP), primary industry output value (PIOV), secondary industry output value (SIOV) and tertiary industry output value (TIOV), primary industry output value proportion (PPIOV), secondary industry output value proportion (PSIOV), tertiary industry output value proportion (PTIOV), are chosen. Principal component analysis is used to extract four main components from the eight factors which can explain 99.83% of the variance of the eight affecting factors. Then ordinary least square regression is used to analyze the relationship between the four components and carbon dioxide emissions. Finally, we get conclusion: the expansion of the primary industry will lead to higher carbon dioxide emissions. At the same time, compared to the secondary industries, tertiary industry will produce higher carbon dioxide emissions.

Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition

Using the data at the county level and the regional gravity center model, we calculated six key socio-economic gravity centers, namely population, GDP, output values of primary, secondary and tertiary industries, and arable land area in the Tarim River Basin for each year from 1980 to 2009. We inspected the spatial dynamics of these centers and found that the gravity centers of population and economy evolved simultaneously. The disproportional growth between the population and the economy is also analyzed. The results show that: 1) The gravity centers of the GDP, the output values of the main three industries and arable land area show migration trending from southwest to northeast, while the population gravity center shows an excessive growth in the southwest during the same time period. The migration amplitude of the GDP and output values of primary industry, secondary industry, tertiary industry are measurably higher than that of the population. 2) The population gravity center has a negative correlation with the gravity centers of secondary and tertiary industries output values in both longitudinal and latitudinal directions, and a positive correlation with that of primary industry output value in the longitudinal direction. Based on the analysis of correlation coefficient and offset distance, the imbalance between the population and the economy has increased since the 1980s, with regional economic differences now exceeding the international cordon.

Comprehensive quantitative evaluation of the water resource carrying capacity in Wuhan City based on the “human–water–city” framework: Past, present and future

基于LMDI分解的厦门市碳排放强度影响因素分析

National key towns are one of the most important units for mitigating China's carbon emissions from urbanisation, industrialisation and agricultural modernisation under China's rural revitalisation strategy. The rise in the carbon footprint (CF) corresponding to increasing populations and energy consumption in national key towns has not been underestimated. This paper aims to explore the impact of local resident energy consumption on the degree of coordination between ecology and the economy. To achieve this objective, the carbon pressure index (CPI), carbon occupancy index (COI) and eco-economic coordination index (EECI) are constructed by applying the CF, carbon carrying capacity (CC) and carbon deficit (CD) of Caijiapo Town from 2012 to 2017. Furthermore, the relationship between the CF, economic growth and per capita disposable income is described based on the decoupling index (DI). The results reveal that, apart from a decline in 2014, the per capita CF of Caijiapo Town has increased, with an average annual growth rate of 16.80%. The CF of different energy sources shows that the CF of natural gas is much larger than those of raw coal, oil and electricity. The DI between GDP, the per capita disposable income of urban and rural residents and the resident energy CF first decreases and then increases. The DI between GDP, the per capita disposable income of urban residents and the resident energy CF is 1.09 and 1.72, and urban residents are the main contributors to the resident energy CF from 2015 to 2017. The CPI and COI show an upward trend, and the eco-economic coordination index (EECI) of Caijiapo Town undergoes a change from poor coordination (grade II) to worst coordination (grade I) from 2012 to 2017. Therefore, the following suggestions are proposed: the CC should be treated as a constraint, energy utilisation should be improved, residents' consumption structure should be optimised, differentiated policies should be implemented for the energy consumption of urban and rural residents and a spatial planning system and operational mechanism should be established that combines multiple regulations into a single regulation.

An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China. Based on the perspective of industrial structure, the expanded KAYA equation to measure the energy related carbon emissions of the primary industries (Resources and Agriculture) and secondary industries (Manufacturing and Construction) and tertiary industries (Retail and Service) was utilized in Shandong Province from 2011 to 2017. The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach. The results were follows: (1) Under the three industrial dimensions, the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries. (2) The development level effect and the employment scale effect play a pulling role in carbon emissions. (3) From the perspective of the employment structure effect of the primary industry, there is a restraining effect on carbon emissions, while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions, and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry.

The article constructs the VAR model, and empirically studies the interaction between per capita travel expenditure and disposable income of Chinese urban residents through impulse response function and variance decomposition method. The conclusion of the study shows that there is a long-term dynamic cointegration relationship between tourism expenditures and disposable income of urban residents in China, but the promotion between them is not enough.

Guangdong Province is one of the provinces in China with a developed paper industry， and accurately predicting carbon emissions from the paper industry in Guangdong Province and formulating reasonable and effective carbon emission reduction measures have a significant impact on achieving the carbon peaking and carbon neutrality goals of China's paper industry. To this end， total industrial output value， employment scale， per capita industrial output value， carbon productivity， energy intensity， and energy structure indicators were introduced to construct the extended stochastic environmental impact assessment （STIRPAT） model， the partial least squares method was used for regression analysis， and the carbon emissions of Guangdong's paper industry from 2023 to 2050 under four scenarios were predicted. The study produced several results： ① Total industrial output value， per capita industrial output value， employment scale， and energy intensity are positively correlated with carbon emissions， whereas carbon productivity and energy structure are negatively correlated with carbon emissions. ②Under the baseline scenario， the paper industry can only achieve carbon peaking in 2040； under the low-carbon development scenario， although the paper industry can achieve carbon peaking by 2030， its carbon emissions will remain between 16.147 Mt and 19.337 Mt by 2050； under the strong low-carbon development scenario， the paper industry can not only achieve carbon peaking by 2030 but is also expected to achieve carbon neutrality by 2060. ③Under the fast development scenario， the carbon emissions of the paper industry maintain an upward trend， and the carbon emissions reach a high level in 2050， making it basically impossible to achieve the "dual carbon" goal. Therefore， Guangdong's paper industry should rationally plan the development of its paper production scale， actively enhance carbon productivity， optimize energy structure， and promote green technological advancements in the industry， thereby driving green and sustainable development of the paper industry.

With the support of the total output of primary industry, secondary industry and tertiary industry and industry value of cultivating industry, forestry industry, animal husbandry industry and fishery industry of 19 country-level units in Yellow River Delta in 2007, the paper calculated the variation index of economic development based on country level, the MDS analysis was explored for primary industry, secondary industry and tertiary industry and compared with spatial difference characteristics of 19 country-level units in Yellow River Delta. The study carried out the analysis of combination analysis of primary, secondary and tertiary industry, and optimized the cultivating industry, forestry, animal husbandry and fishery industry. Autocorrelation characteristics was clarified by Moran‘s I calculation, the new development mode of agricultural industrial structure was systemically concluded that the different mode presented in the different country units. The results showed that the industry evolution stage of primary, secondary and tertiary industry structure of 19 country units is in primary and tertiary industries stage and secondary, primary and tertiary industries stage according to industry structure stages theory, the obvious characteristics is that the cultivating industry value has spatial variability based on classical statistics combinig with universal Kriging. The emphasis of industry adjustment should be the focus on the secondary industry driving transformation into the primary, secondary and tertiary industries jointly driving economic growth, straight-pushing mode and tilting mode were put forward to new ideas about promoting industrial optimization and coordination development in Yellow River Delta. The study drew a conclusion that the measures were took to optimize industrial structure of cultivating industry, forestry industry, animal husbandry and fishery industry by combing straight-pushing mode with tilting mode, during the coordination development, focused on association effects of land and marine industry, extended agriculture industrialization chain and formed the diversification mode.

With the rapid development of computer technology, GIS technology has been widely used in the field of spatial geographic information, and the research on spatial analysis is becoming more and more important. This paper uses GIS and mathematical statistics to analyze Guilin's total tourism consumption and per capita disposable income of urban residents. Based on the analysis of the overall consumption data of Guilin tourism and the per capita disposable income of urban residents, this paper draws the following conclusions: 1) The main income of Guilin tourism economy comes from the southwest, which is one of the main reasons for the large gap between the per capita disposable income of urban residents in the southwest and the northeast. 2) The average annual growth value of Guilin's total tourism consumption and per capita disposable income of urban residents between 2012 and 2019 was 21.63 x 1010 yuan·a-1 and 2054.07 yuan·a-1. 3) The development of tourism in southwest Guilin has obviously affected the local economy, so that the per capita disposable income of urban residents has increased. 4) The tourism development in Northeast Guilin is lagging behind, and the economic income level is relatively low. There is a large gap in the per capita disposable income of urban residents in the southwest and northeast. The research results of this paper are intended to provide reference opinions for related researchers.

Developing Financial Inclusion is one of the important ways to build a moderately prosperous society. Financial Inclusion can expand the coverage of financial services, deepen the penetration of financial services, and provide efficient financial products for different levels of individuals and institutions. In recent years, scholars have studied the concept of Financial Inclusion, dimensional composition, the relationship with economic growth, income distribution and targeted poverty alleviation. However, this paper argues that a more comprehensive and detailed framework is needed to understand the mechanism of Financial Inclusion. With the development of digital technology, it is of great practical significance to explore the influence mechanism of digital Financial Inclusion to promote the economic development of our country, especially to enhance the income of urban and rural residents. In this study, we use massive data to compile financial inclusive index, and divide the digital Financial Inclusion into three dimensions, that is, coverage, depth of use and degree of digitalization, to study the impact of digital Financial Inclusion on the income of Chinese residents. Meanwhile, in the case of distinguishing different regions, urban and rural areas, we explore the difference of the impact of digital Financial Inclusion on the income of Chinese residents. In addition, we also use the number of provincial Internet sites as a tool variable of the digital Financial Inclusive index to estimate the 2SLS to control the endogenous problems in the measurement model. The research finds that: First, digital Financial Inclusion has significantly improved the per capita disposable income of urban and rural residents in China, and the effect of digital Financial Inclusion on the per capita disposable income of urban residents is significantly greater than that of rural residents. Second, digital inclusive finance has significantly improved the income of urban and rural residents by promoting economic growth and entrepreneurial behavior.Third, in the analysis of the three dimensions of digital Financial Inclusion, the role of each dimension has a differentiated impact. Fourth, the effect of digital Financial Inclusion on the per capita disposable income of the eastern residents is greater than that of the central and western residents. The conclusion of this paper has certain guiding significance for understanding the actual value of digital Financial Inclusion, promoting the development of digital Financial Inclusion and improving the income of urban and rural residents in China.

Studies on carbon dioxide (CO2) emissions at provincial level can provide a scientific basis for the optimal use of energy and the formulation of CO2 reduction policies. We studied the variation of CO2 emissions of primary energy consumption and its influencing factors based on data in Xinjiang Uygur autonomous region from 1952 to 2008, which were calculated according to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Xinjiang’ CO2 emission process from 1952 to 2008 could be divided into five stages according to the growth rates of total amount of CO2 emissions and CO2 emission intensity. The impact factors were quantitatively analyzed using Logarithmic Mean Divisia Index (LMDI) method in each stage. Various factors, including government policies and technological progress related to the role of CO2 emissions, were comprehensively analyzed, and the internal relationships among various factors were clarified. The results show that the contribution rates of various impact factors are different in each stage. Overall, economic growth and energy consumption intensity were the main driving factors for CO2 emissions. Since the implementation of the birth control policy, the driving force of population growth on the increase in CO2 emissions has slowly weakened. The energy consumption intensity was further affected by the industrial structure and energy consumption intensity of primary, secondary and tertiary industries, with the energy consumption intensity of the secondary industries and the proportion of secondary industries being the most important factors affecting the energy consumption intensity. Governmental policies and technological progress were also important factors that affected CO2 emissions.